EdinburghNLP/xsum
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How to use wy3106714391/t5-small-finetuned-xsum with Transformers:
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("wy3106714391/t5-small-finetuned-xsum")
model = AutoModelForSeq2SeqLM.from_pretrained("wy3106714391/t5-small-finetuned-xsum")This model is a fine-tuned version of t5-small on the xsum dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.6682 | 1.0 | 12753 | 2.4400 | 28.7524 | 8.1221 | 22.6965 | 22.6964 | 18.8131 |
| 2.6078 | 2.0 | 25506 | 2.4006 | 29.4484 | 8.5941 | 23.308 | 23.3037 | 18.8087 |
| 2.6137 | 3.0 | 38259 | 2.3878 | 29.5769 | 8.7047 | 23.446 | 23.4444 | 18.8262 |
Base model
google-t5/t5-small